Multi-adjoint based group decision-making under an intuitionistic fuzzy information system

Abstract

The construction of belief intervals is crucial for decision-making in multi-attribute group information integration. Based on multi-adjoint and evidence theory, an approach to multi-criteria group decisionmaking(MCGDM) in intuitionistic fuzzy information system is proposed. First, the upper and lower approximations of alternatives are calculated by multi-adjoint operators under the correlation matrices which were given by different experts. After that the belief and plausibility functions are gained by intuitionistic fuzzy probability formulas. Second, the belief intervals of alternatives are acquired by combining all experts' evidence. Then the alternatives are ranked by comparing the belief intervals. Finally, the effectiveness of the method is verified by an application of business transaction. Compared with the existing model, the method introduced in this paper is more effective and accurate.

A Novel Approach for Ranking Intuitionisitc Fuzzy Numbers and its Application to Decision Making

“…According to the information contained by different attributes, decision makers (DMs) need to sort the alternatives of the discourse or select the optimal alternative form the universe of discourse. Here, we consider an evaluation example of house selling taken from [20], which is described as follows.…”

“…Example 6 According to literature [20], multi-adjoint theory and Dempster-Shafer evidence theory are applied to tackle the multi-attribute group decision making problem. The main MADM ranking process can be explained as Belief structure construction-Evidence combination-Belief internal comparison.…”

“…Therefore, it is more delicate in describing the fuzziness of the real wrold and more flexible in dealing with the uncertainty. At present, the theoretical and practical application of IF-S have been deeply and attentively studied and have been widely used in many application fields [10,18,33], such as medicine diagnosis [8,11], multi-attribute decision making [9,20,34,38], cluster analysis [5,19,36], With the in-depth study of IFS in the application field, many pioneering works have been focused on comparing and ranking intuitionistic fuzzy numbers (IFNs) [32]. A large number of scholars make great efforts in constructing different measures to rank IFSs (IFNs) and apply them to practical problems.…”

Intuitionistic fuzzy MABAC method based on cumulative prospect theory for multiple attribute group decision making

“…For example, the conclusion that the product meets the needs of buyers is based on the analysis and evaluation of multiple aspects of the product, such as price, durability, and other aspects 36–38 . In addition, the problem of MADM is also reflected in the business activities 39–42 . Even a small restaurant also faces with the evaluation of raw material suppliers from multiple perspectives.…”

House of Quality-Based Analysis of New Service Development Using Context Free Grammar Evaluation-Enhanced Fuzzy Hybrid Modelling

“…However, intuitionistic fuzzy sets are a well-known extension of fuzzy sets that have, to date, once again become a hot topic in the decision-making area [54,55]. They have several advantages, for example, they provide the extreme limits for the belongingness and non-belongingness elements and construct the vague sets more accurately [56].…”